Ambulatory monitoring of physiologic response to valsalva maneuver

ABSTRACT

Systems and methods for monitoring physiologic response to Valsalva maneuver (VM) are disclosed. An exemplary patient monitor may detect a natural incidence of a VM session occurred in an ambulatory setting using a heart sound (HS) signal sensed from the patient. The patient monitor may include a physiologic response analyzer to sense patient physiologic response during the detected VM session, and generate a cardiovascular or autonomic function indicator based on the sensed physiologic response to the VM. Using the physiologic response to the VM, the system may detect a target physiologic event using the sensed physiologic response to the VM.

CLAIM OF PRIORITY

This application is a continuation of U.S. Pat. Application Serial No.16/515,740, filed on Jul. 18, 2019, which claims the benefit of priorityunder 35 U.S.C. § 119(e) of U.S. Provisional Pat. Application SerialNumber 62/714,413, filed on Aug. 3, 2018, which are herein incorporatedby reference in their entireties.

TECHNICAL FIELD

This document relates generally to medical devices, and moreparticularly, to systems, devices and methods for ambulatory detectionof Valsalva maneuver and monitoring physiologic response to Valsalvamaneuver.

BACKGROUND

Valsalva maneuver (VM) is a technique typically performed when oneattempts to exhale forcefully against a closed airway, such as byclosing one’s mouth or pinching one’s nose shut. The VM can occurunintentionally or intentionally. Natural incidence of VM may occur whensneezing, coughing, passing stool during constipation, vomiting, liftingheavy objects (e.g., weightlifting or other fitness regimes), or gettingup from the bed. VM technique has been used to equalize the ear pressureduring activities like scuba diving, flight landing, parachuting etc.

The VM can increase pressures inside the nasal sinuses and the chestcavity within a short period of time. Sustained elevated chest pressuremay stimulate the vagus nerve and increase vagal tone. Physiologicresponse to the VM typically consists of four phases. In Phase I,blowing against a closed airway increases the pressure inside the chestcavity, which immediately pushes blood from the pulmonary circulationinto the left atrium of the heart. This causes a mild rise in strokevolume during the first few seconds of the maneuver. Phase II ischaracterized by reduced venous return and compensation. The increasedpressure in the chest cavity prevents any more blood from returning theheart from the rest of the body. As such, stroke volume suddenly falls,and cardiac output reduces. To compensate for the drop in cardiacoutput, the body’s blood vessels constrict, and blood pressure rises.This elevated blood pressure continues for the duration of the Valsalvamaneuver. In certain cases, the compensation can be quite marked withpressure returning to near or even above normal. However, the cardiacoutput and blood flow to the body remains low. During this time, thepulse rate increases (compensatory tachycardia). Phase III is a pressurerelease phase, during which the pressure on the chest is released,allowing the pulmonary vessels and the aorta to re-expand, which causesa further initial slight fall in stroke volume due to decreased leftatrial return and increased aortic volume, respectively. Venous bloodcan once more enter the chest and the heart, and the cardiac outputbegins to increase. Finally, in Phase IV, the blood flow to the heartand lungs returns to normal, as does the cardiac output and bloodpressure. The blood return may be enhanced by the effect of entry ofblood that had been dammed back, causing a rapid increase in cardiacoutput. In some instances, the stroke volume may rise above normalbefore returning to a normal level. With return of blood pressure, thepulse rate returns towards normal.

Valsalva maneuver has been used as a diagnostic tool or a treatment aid.In an example, the VM can be used to evaluate cardiac function orautonomic nervous control of the heart. Deviation from typical responsepattern of a normal healthy subject may indicate heart anomaly, orabnormal autonomic nervous control of the heart. For example,cardiovascular response to the VM may be used to evaluate cardiacfilling pressure in patients with congestive heart failure (CHF). VM mayalso induce changes in cerebrovascular variables within a short timespan, which can be used to assess cerebral autoregulatory function byprovoking blood pressure changes. Other diagnostic applications includeailments related to an autonomous nervous system, nerve tissue injury inthe cervical spine region, hernia, pelvic floor weakness, cerebrospinalfluid leak, intrinsic sphincteric deficiency, or abnormal connectionsbetween the mouth and maxillary sinuses (oroantral fistulas) after atooth extraction, among others. Apart from applications in medicaldiagnostics, the VM has also been used as a treatment aid, such as toclear mucus and relieve pain in sinusitis, expel pus from a clogged earin middle ear infection, interrupt palpitations such as supraventriculartachycardia, stop hiccups, etc.

OVERVIEW

The VM has been used clinically to evaluate various cardiovascular andneurological disorders, an example being detection and assessment ofsyncope. Syncope is generally characterized by an abrupt loss ofconsciousness with a concomitant loss of postural tone. Decreasedcerebral perfusion is common to all causes of syncope. For example,positional change from supine to erect causes a 300-to 800-millilitershift in blood volume from the thoracic cavity to the lower extremities.Although cerebrovascular autoregulation in healthy subjects help ensureenough cerebral blood flow independent of systemic blood pressure, olderpatients and those with chronic hypertension or cardiovascular diseasesmay be susceptible to syncope when a relatively small decrease insystemic blood pressure occurs.

Based on the underlying causes, syncope may have three major types:cardiogenic, orthostatic, and neurally mediated syncope. Cardiogenicsyncope is associated with significantly higher rates of morbidity andmortality than other causes. Patients with underlying cardiac disease,such as cardiac arrhythmias or structural cardiopulmonary diseases, areat higher risk for recurrent syncope than are other syncope patients.Patients with syncope are more likely to have coronary artery orcerebrovascular disease and to take cardiac or antihypertensivemedications than patients without syncope. Orthostatic syncope isassociated with orthostatic hypotension (OH), characterized by a drop inblood pressure of at least 20 millimeters of mercury (mmHg) systolic or10 mmHg diastolic within about three minutes of standing. Tachycardiaand a heart rate greater than 100 beats per minute during testingindicate volume depletion. Minimal cardiac acceleration suggestsbaroreflex impairment may contribute to orthostatic syncope. Neurallymediated syncope, also known as vasovagal syncope (WS), orneuro-cardiogenic syncope, is a disorder of the autonomic regulation ofpostural tone, and may be related to vasovagal, carotid sinus, orsituational causes of hypotension. In healthy subjects, upon positionalchange, a series of complex neurohormonal events would maintain cerebralperfusion. For example, decreased venous return and subsequent decreasedleft ventricular filling may result in increased sympathetic tone and ahypercontractile left ventricle. However, overly sensitive leftventricular receptors may misinterpret hypercontractility as volumeoverload and falsely inhibit sympathetic stimulation while promotingparasympathetic drive, resulting in hypotension and syncope.

While the cardiogenic syncope constitutes only approximately 15 percentof overall syncope population, the majority of syncope are non-cardiacin nature, including about 60 percent being neurally mediated syncope,and about 15 percent being orthostatic syncope. Identifying the cause ortype of syncope, such as a differential diagnosis of non-cardiac orunexplained syncope (e.g., distinguishing orthostatic syncope from WS),may be clinically desired for improved patient management and treatment.Physiologic response to VM as discussed in this document may improvedifferential diagnosis of syncope. For example, patients with OH may notbe able to produce sufficient increase in sympathetically mediatedvasoconstriciton following initial hypotension. These patients typicallylack BP recovery at the late Phase II of MV and BP overshoot at thePhase IV of MV. Instead, the BP slowly drifts back up to baseline afterthe Valsalva-induced hypotension.

Currently, VM induction and VM response assessment are typically carriedout in a clinical setting, where the patient is required to be sedentarywith VM testing and analysis equipment attached to the patient. This canbe less convenient for ambulatory patients who require ambulatorymonitoring for syncope. Additionally, in-clinic syncope evaluation, suchas orthostatic challenge or tilt-table test to identify the nature of asyncope episode occurred in the past, at least because the in-clinictests that attempt to mimic the OH may not adequately reproduce thehemodynamic profile of the past spontaneous syncope from onset to fulldevelopment. The tilt table test may have substantial false negativerate for detecting syncope onset in a clinical test. At least becausemany syncopal events occur abruptly and unexpectedly in an ambulatorysetting, ambulatory syncope monitoring or and differential diagnosis ofsyncope types, based on naturally occurring VM sessions, may beclinically advantageous in some patients. For these reasons, the presentinventors have recognized that there is a need for improved systems,devices, and methods for ambulatory VM monitoring and clinical diagnosisbased on patient ambulatory VM responses.

This document discusses, among other things, systems, devices, andmethods for monitoring patient physiologic response to the VM. Anexemplary patient monitor includes a VM detector circuit to detect a VMsession, such as a naturally occurring VM incidence, using a heart sound(HS) signal sensed from the patient. The patient monitor may include aphysiologic response analyzer circuit to sense a physiologic response tothe detected VM session, and generate a cardiovascular or autonomicfunction indicator based on the physiologic response to the VM. Thesystem can generate medical diagnostics such as a syncope of aparticular type, a worsening heart failure (WHF) event, or aconstipation episode.

Example 1 is a system for monitoring a physiologic response to aValsalva maneuver (VM) in a patient. The system comprises a VM detectorcircuit configured to detect a VM session using a heart sound (HS)signal sensed from the patient, a physiologic response analyzer circuitconfigured to sense a physiologic signal during the detected VM session,and a physiologic event detector configured to detect a targetphysiologic event using the sensed physiologic signal during thedetected VM session.

In Example 2, the subject matter of Example 1 optionally includes the VMdetector circuit configured to recognize one or more VM phases using aHS metric based on one or more of first (S1), second (S2), third (S3),or fourth (S4) heard sound component from the sensed HS signal, the VMphase including sequentially arranged first, second, third, or fourth VMphases.

In Example 3, the subject matter of Example 2 optionally includes the VMdetector circuit configured to detect one or more of: the first VM phaseusing an increase in S1 intensity and a decrease in S2 intensity: thesecond VM phase using a decrease in S1 intensity and an increase in S2intensity; or the fourth VM phase using an increase in S1 intensity andan increase in S2 intensity.

In Example 4, the subject matter of any one or more of Examples 2-3optionally includes the VM detector circuit configured to detect one ormore of: the first VM phase using an increase in S3 intensity or anincrease in S4 intensity; or the third VM phase using a decrease in S3intensity or a decrease in S4 intensity.

In Example 5, the subject matter of any one or more of Examples 2-4optionally includes the VM detector circuit configured to detect the VMsession further using one or more of: a physical activity level below aspecific threshold; an upright posture; or a respiratory pause.

In Example 6, the subject matter of any one or more of Examples 2-5optionally includes the physiologic response analyzer circuit configuredto generate a cardiovascular or autonomic function indicator using thesensed physiologic signal during the detected VM session, the sensedphysiologic signal includes one or more of a HS signal and a heart ratesignal.

In Example 7, the subject matter of Example 6 optionally includes thephysiologic response analyzer circuit configured to generate thecardiovascular or autonomic function indicator using a comparison of thesensed physiologic signal during the detected VM session to a Valsalvaresponse template at one or more of the VM phases.

In Example 8, the subject matter of any one or more of Examples 2-7optionally includes the physiologic response analyzer circuit configuredto detect S3 intensity and S4 intensity from a HS signal sensed duringthe detected VM session, and to generate a diastolic dysfunctionindictor using a ratio of the S3 intensity to the S4 intensity.

In Example 9, the subject matter of Example 8 optionally includes thephysiologic event detector configured to detect a worsening heartfailure (WHF) event using the generated diastolic dysfunction indictor.

In Example 10, the subject matter of any one or more of Examples 6-7optionally includes the physiologic event detector configured to detecta syncope using the generated cardiovascular or autonomic functionindicator.

In Example 11, the subject matter of Example 10 optionally includes thecardiovascular or autonomic function indicator that may include aValsalva ratio using heart rates measured during the detected VMsession, and the physiologic event detector may be configured to detecta vasovagal syncope using the generated Valsalva ratio.

In Example 12, the subject matter of Example 10 optionally includes thecardiovascular or autonomic function indicator that may include a S2intensity trend during the detected VM session, and the physiologicevent detector may be configured to detect an orthostatic syncope usingthe generated S2 intensity trend.

In Example 13, the subject matter of any one or more of Examples 2-7optionally includes the physiologic event detector configured to detectthe target physiologic event including a constipation episode.

In Example 14, the subject matter of any one or more of Examples 1-13optionally includes a therapy circuit configured to initiate or adjust atherapy to the patient in response to the detected target physiologicevent.

In Example 15, the subject matter of any one or more of Examples 1-14optionally includes an ambulatory medical device (AMD) including the VMdetector circuit and the physiologic response analyzer circuit, the AMDconfigured to monitor a patient physiologic response to the detected VMsession.

Example 16 is a method for monitoring a physiologic response to aValsalva maneuver (VM) in a patient. The method comprises steps of:detecting a VM session using a heart sound (HS) signal sensed from thepatient; sensing a physiologic signal during the detected VM session;and detecting a target physiologic event using the sensed physiologicsignal during the detected VM session.

In Example 17, the subject matter of Example 16 optionally includesdetecting the VM session that may include recognizing one or more VMphases using a HS metric based on one or more of first (S1), second(S2), third (S3), or fourth (S4) heard sound component from the sensedHS signal, the VM phase including sequentially arranged first, second,third, or fourth phases.

In Example 18, the subject matter of Example 17 optionally includesrecognizing the one or more VM phases that may include detecting one ormore of: the first VM phase using an increase in S1 intensity and adecrease in S2 intensity, or an increase in S3 intensity or an increasein S4 intensity; the second VM phase using a decrease in S1 intensityand an increase in S2 intensity; the third VM phase using a decrease inS3 intensity or a decrease in S4 intensity; or the fourth VM phase usingan increase in S1 intensity and an increase in S2 intensity.

In Example 19, the subject matter of any one or more of Examples 16-18optionally includes detecting a VM session that may include detectingone or more of: a physical activity level below a specific threshold; anupright posture; or a respiratory pause.

In Example 20, the subject matter of any one or more of Examples 16-19optionally includes generating a cardiovascular or autonomic functionindicator using a comparison of the sensed physiologic signal during thedetected VM session to a Valsalva response template, the sensedphysiologic signal includes one or more of a HS signal and a heart ratesignal.

In Example 21, the subject matter of Example 20 optionally includesdetecting the target physiologic event that may include detecting asyncope using the generated cardiovascular or autonomic functionindicator.

In Example 22, the subject matter of any one or more of Examples 16-21optionally includes detecting the target physiologic event that mayinclude: detecting S3 intensity and S4 intensity from a HS signal sensedduring the detected VM session; generating a diastolic dysfunctionindictor using a ratio of the S3 intensity to the S4 intensity; anddetecting a worsening heart failure (WHF) event using the generateddiastolic dysfunction indictor.

In Example 23, the subject matter of any one or more of Examples 16-22optionally includes initiating or adjusting a therapy to the patient inresponse to the detected target physiologic event.

The systems, devices, and methods discussed in this document may improvethe technology of ambulatory monitoring of physiologic response to VM,and detection of patient cardiovascular or neurological condition basedon the ambulatory VM response. Discussed herein includes detecting andassessing a physiologic, naturally occurring VM session using heartsounds (HS). The present inventors have recognized that various HSmetrics are indicative of or correlated with hemodynamic profiles atvarious VM phases (e.g., one or more of Phases I-IV). As such, using HSis advantageous in recognizing a deviation from a normal physiologicresponse at one or more VM phases. Compared to conventional in-clinicapproach of inducing VM and analyzing patient cardiovascular response tothe VM, the systems and methods discussed in this document may be moresuitable for patients with such medical conditions that requireambulatory monitoring, such as WHF events and syncope episodes. TheHS-based VM response monitor may improve the performance of aphysiologic event detector, with a higher sensitivity and specificityfor detecting events such as WHF or syncope episodes. This may helpensure timely medical attention to patients and medical intervention asneeded, and reduce unnecessary medical interventions (e.g., drugs,procedures, or device therapies) to those patients identified to be freeof the medical events or have a low risk of developing such events inthe future. Additionally, the HS-based VM monitoring and differentialdiagnosis of syncope may help ensure individualized syncope therapy. Assuch, the devices and methods discussed herein would not only betteralign the medical resources to serve the need of more patients, but mayalso achieve overall system cost savings for chronically monitoringsyncope patients.

The systems, devices, and methods discussed in this document may alsoimprove functionality of a medical device or a patient managementsystem. Conventional cardiovascular monitoring during the VM may put ahigh demand for battery power, storage space, computing and processpower, and communication bandwidth. In contrast, HS sensors have beenused for ambulatory cardiac monitoring. HS sensors can be non-invasivelyattached to the patient. The HS-based VM response detection discussedherein requires little extra hardware beyond what an ambulatory cardiacmonitor may generally provide. Therefore, the HS-based VM monitoringsystem discussed herein provides a power- and resource-conservativesolution to ambulatory VM response monitoring.

This Overview is an overview of some of the teachings of the presentapplication and not intended to be an exclusive or exhaustive treatmentof the present subject matter. Further details about the present subjectmatter are found in the detailed description and appended claims. Otheraspects of the disclosure will be apparent to persons skilled in the artupon reading and understanding the following detailed description andviewing the drawings that form a part thereof, each of which are not tobe taken in a limiting sense. The scope of the present disclosure isdefined by the appended claims and their legal equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments are illustrated by way of example in the figures ofthe accompanying drawings. Such embodiments are demonstrative and notintended to be exhaustive or exclusive embodiments of the presentsubject matter.

FIG. 1 illustrates generally an example of a patient monitor system andportions of an environment in which the system may operate.

FIG. 2 illustrates generally an example of a Valsalva maneuver (VM)detector and analyzer system configured to detect a VM session andevaluate patient physiologic response to the VM.

FIG. 3 illustrated generally an example of a portion of a VM detectionsystem that detects a VM session using heart sounds and informationabout patient functional states.

FIGS. 4A-C illustrate generally examples of VM-based physiologic eventdetectors configured to detect various physiologic events usingphysiologic response to the VM.

FIG. 5 illustrates generally an example of a method for monitoring aphysiologic response to VM in a patient.

FIG. 6 illustrates generally a block diagram of an example machine uponwhich any one or more of the techniques (e.g., methodologies) discussedherein may perform.

DETAILED DESCRIPTION

Disclosed herein are systems, devices, and methods for monitoringphysiologic response to Valsalva maneuver (VM). An exemplary patientmonitor may detect a natural incidence of VM session using a heart sound(HS) signal sensed from the patient. The patient monitor includes aphysiologic response analyzer circuit that can sense patient physiologicresponse during the detected VM session, and generate a cardiovascularor autonomic function indicator based on the sensed physiologic responseto the VM. Based on the physiologic response, the system may detect atarget physiologic event.

FIG. 1 illustrates generally an example of a patient monitor system 100and portions of an environment in which the system 100 may operate. Thepatient monitor system 100 may chronically monitor a patient 102 todetect and evaluate a syncopal event. Portions of the system 100 may beambulatory. Portions of the system 100 may be disposed in the patient’shome or office, a hospital, clinic, or physician’s office. The patientmonitor system 100 may include an ambulatory system 105 associated withthe patient 102, an external system 125, and a telemetry link 115providing for communication between the ambulatory system 105 and theexternal system 125.

The ambulatory system 105 may include an ambulatory medical device (AMD)110. In an example, the AMD 110 may be an implantable devicesubcutaneously implanted in a chest, abdomen, or other parts of thepatient 102. Examples of the implantable device may include, but are notlimited to, pacemakers, pacemaker/defibrillators, cardiacresynchronization therapy (CRT) devices, cardiac remodeling controltherapy (RCT) devices, neuromodulators, drug delivery devices,biological therapy devices, diagnostic devices such as cardiac monitorsor loop recorders, or patient monitors, among others. The AMD 110alternatively or additionally may include a subcutaneous medical devicesuch as a subcutaneous monitor or diagnostic device, external monitoringor therapeutic medical devices such as automatic external defibrillators(AEDs) or Holter monitors, or wearable medical devices such aspatch-based devices, smart wearables, or smart accessories.

By way of example, the AMD 110 may be coupled to a lead system 108. Thelead system 108 may include one or more transvenously, subcutaneously,or non-invasively placed leads or catheters. Each lead or catheter mayinclude one or more electrodes. The arrangements and uses of the leadsystem 108 and the associated electrodes may be determined using thepatient need and the capability of the AMD 110. The associatedelectrodes on the lead system 108 may be positioned at the patient’sthorax or abdomen to sense a physiologic signal indicative of cardiacactivity, or physiologic response to diagnostic or therapeuticstimulations to a target tissue. By way of example and not limitation,and as illustrated in FIG. 1 , the lead system 108 may be surgicallyinserted into, or positioned on the surface of, a heart 101. Theelectrodes on the lead system 108 may be positioned on a portion of aheart 101, such as a right atrium (RA), a right ventricle (RV), a leftatrium (LA), or a left ventricle (LV), or any tissue between or near theheart portions. In some examples, the lead system 108 and the associatedelectrodes may alternatively be positioned on other parts of the body tosense a physiologic signal containing information about patient heartrate or pulse rate. In an example, the ambulatory system 105 may includeone or more leadless sensors not being tethered to the AMD 110 via thelead system 108. The leadless ambulatory sensors may be configured tosense a physiologic signal and wirelessly communicate with the AMD 110.

The AMD 110 may include a hermetically sealed can that houses one ormore of a sensing circuit, a control circuit, a communication circuit,and a battery, among other components. The sensing circuit may sense aphysiologic signal, such as by using a physiologic sensor or theelectrodes associated with the lead system 108. The physiologic signalsmay contain information about patient physiologic response to aprecipitating event associated with onset of a future syncopal event.The physiologic signal may represent changes in patient hemodynamicstatus. Examples of the physiologic signal may include one or more ofelectrocardiogram, intracardiac electrogram, arrhythmia, heart rate,heart rate variability, intrathoracic impedance, intracardiac impedance,arterial pressure, pulmonary artery pressure, left atrial pressure,right ventricular (RV) pressure, left ventricular (LV) coronarypressure, coronary blood temperature, blood oxygen saturation, one ormore heart sounds, intracardiac acceleration, physical activity orexertion level, physiologic response to activity, posture, respirationrate, tidal volume, respiratory sounds, body weight, or bodytemperature.

The AMD 110 may include a Valsalva maneuver (VM) response analyzercircuit 160 that can detect a VM session such as a naturally occurringVM incidence, and evaluate patient physiologic response to the VM. TheVM session may be detected using a heart sounds (HS) signal sensed fromthe patient. HS metrics, indicative of or correlated to hemodynamicprofiles during the VM, may be generated from the HS signal. The VMresponse analyzer circuit 160 may use the HS metrics to determine adeviation from a normal VM response at one or more VM phases. The VMresponse analyzer circuit 160 may sense patient physiologic response tothe detected VM session, and generate a cardiovascular or autonomicfunction indicator, detect a target physiologic event such as WHF, heartmurmur, syncope, or constipation. Examples of detecting the VM, anddetecting a physiologic event using the physiologic response to the VM,are discussed below, such as with reference to FIGS. 2-4 .

The AMD 110 may include a therapy circuit configured to generate anddeliver a therapy to the patient, such as in response to the detectedphysiologic event. Examples of the therapy may include electrical,magnetic, or other forms of therapy. In some examples, the patientmonitor system 100 may include a drug delivery system, such as a druginfusion pump, to deliver medication, such as diuretics or vasodilatorsfor treating or alleviating symptoms of HF. The AMD 110 may trend thephysiologic response to the VM over time, and use said trend to assessprogression of a medical condition (e.g., WHF), predict a risk of afuture event (e.g., HF decompensation, or syncope), assess a therapeuticeffect of a therapy (e.g., a device therapy such as provided by the AMD110, or a drug therapy such as provided by the drug delivery system116), or modify a therapy if needed.

The external system 125 may include a dedicated hardware/software systemsuch as a programmer, a remote server-based patient management system,or alternatively a system defined predominantly by software running on astandard personal computer. The external system 125 may manage thepatient 102 through the AMD 110 connected to the external system 125 viaa communication link 115. This may include, for example, programming theAMD 110 to perform one or more of acquiring physiologic data, performingat least one self-diagnostic test (such as for a device operationalstatus), analyzing the physiologic data to detect VM and a targetphysiologic event, or optionally delivering or adjusting a therapy tothe patient 102. The external system 125 may communicate with the AMD110 via the communication link 115. The device data received by theexternal system 125 may include real-time or stored physiologic datafrom the patient 102, diagnostic data such as cardiovascular orautonomic function indicator or detected physiologic event, responses totherapies delivered to the patient 102, or device operational status ofthe AMD 110 (e.g., battery status and lead impedance). The telemetrylink 115 may be an inductive telemetry link, a capacitive telemetrylink, or a radio-frequency (RF) telemetry link, or wireless telemetrybased on, for example, “strong” Bluetooth or IEEE 802.11 wirelessfidelity “WiFi” interfacing standards. Other configurations andcombinations of patient data source interfacing are possible.

By way of example and not limitation, the external system 125 mayinclude an external device 120 in proximity of the AMD 110, and a remotedevice 124 in a location relatively distant from the AMD 110 incommunication with the external device 120 via a telecommunicationnetwork 122. Examples of the external device 120 may include aprogrammer device. The network 122 may provide wired or wirelessinterconnectivity. In an example, the network 122 may be based on theTransmission Control Protocol/Internet Protocol (TCP/IP) networkcommunication specification, although other types or combinations ofnetworking implementations are possible. Similarly, other networktopologies and arrangements are possible.

The remote device 124 may include a centralized server acting as acentral hub for collected patient data storage and analysis. The patientdata may include data collected by the AMD 110, and other dataacquisition sensors or devices associated with the patient 102. Theserver may be configured as a uni-, multi-, or distributed computing andprocessing system. In an example, the remote device 124 may include adata processor configured to perform further data analysis, such asdetection of a target physiologic event, using the signals received bythe AMD 110. Computationally intensive algorithms, such asmachine-learning algorithms, may be implemented in the remote device 124to process the data retrospectively to confirm, reject, or modify thetarget physiologic event detection provided by the AMD 110. The remotedevice 124 may generate an alert notification. The alert notificationsmay include a Web page update, phone or pager call, E-mail, SMS, text or“Instant” message, as well as a message to the patient and asimultaneous direct notification to emergency services and to theclinician. Other alert notifications are possible.

One or more of the external device 120 or the remote device 124 mayoutput the cardiovascular or autonomic function indicator or thedetected target physiologic event to a system user such as the patientor a clinician. The clinician may review, perform further analysis, oradjudicate the device detection. The detected cardiovascular orautonomic function indicator during the VM, optionally along with the HSmetrics and other physiologic data, may be output to a process includingan instance of a computer program executable in a microprocessor. In anexample, the process may include an automated generation ofrecommendations for initiating or adjusting a therapy, or arecommendation for further diagnostic test or treatment. In an example,the external device 120 or the remote device 124 may include arespective display unit for displaying the physiologic and hemodynamicsignals, or alerts, alarms, emergency calls, or other forms of warningsabout the detection and classification of a syncopal event.

Portions of the AMD 110 or the external system 125 may be implementedusing hardware, software, firmware, or combinations thereof. Portions ofthe AMD 110 or the external system 125 may be implemented using anapplication-specific circuit that may be constructed or configured toperform one or more particular functions, or may be implemented using ageneral-purpose circuit that may be programmed or otherwise configuredto perform one or more particular functions. Such a general-purposecircuit may include a microprocessor or a portion thereof, amicrocontroller or a portion thereof, or a programmable logic circuit, amemory circuit, a network interface, and various components forinterconnecting these components. For example, a “comparator” mayinclude, among other things, an electronic circuit comparator that maybe constructed to perform the specific function of a comparison betweentwo signals or the comparator may be implemented as a portion of ageneral-purpose circuit that may be driven by a code instructing aportion of the general-purpose circuit to perform a comparison betweenthe two signals.

FIG. 2 illustrates generally an example of a Valsalva maneuver (VM)detector and analyzer system 200 configured to detect a VM session andevaluate patient physiologic response to the VM. At least a portion ofthe VM detector and analyzer system 200 may be implemented in the AMD110, the external system 125 such as one or more of the external device120 or the remote device 124, or distributed between the AMD 110 and theexternal system 125.

As illustrated in FIG. 2 , the VM detector and analyzer system 200 mayinclude one or more of a sensing circuit 210, a VM-based event detector220, a user interface 230, and an optional therapy circuit 240. Thesensing circuit 210 may sense a physiologic signal from the patient. Inan example, the sensing circuit 210 may include a sense amplifiercircuit to sense the physiologic signal from a patient via a physiologicsensor, such as an implantable, wearable, or otherwise ambulatory sensoror electrodes associated with the patient. The sensor may beincorporated into, or otherwise associated with an ambulatory devicesuch as the AMD 110. In some examples, the physiologic signals sensedfrom a patient may be stored in a storage device, such as an electronicmedical record (EMR) system. The sensing circuit 210 may receive thephysiologic signal from the storage device, such as in response to auser command or a triggering event. Examples of the physiologic signalsfor detecting the precipitating event may include surfaceelectrocardiography (ECG) sensed from electrodes placed on the bodysurface, subcutaneous ECG sensed from electrodes placed under the skin,intracardiac electrogram (EGM) sensed from the one or more electrodes onthe lead system 108, heart rate signal, physical activity signal, orposture signal, a thoracic or cardiac impedance signal, arterialpressure signal, pulmonary artery pressure signal, left atrial pressuresignal, RV pressure signal, LV coronary pressure signal, coronary bloodtemperature signal, blood oxygen saturation signal, heart sound signal,physiologic response to activity, apnea hypopnea index, one or morerespiration signals such as a respiration rate signal or a tidal volumesignal, brain natriuretic peptide (BNP), blood panel, sodium andpotassium levels, glucose level and other biomarkers and bio-chemicalmarkers, among others. The sensing circuit 210 may include one or moresub-circuits to digitize, filter, or perform other signal conditioningoperations on the received physiologic signal.

In an example, the sensing circuit 210 may include a heart sound (HS)sensor circuit 212 configured to generate one or more HS metrics usingHS information of the patient. The sensing circuit 210 may becommunicatively coupled to a heart sound sensor to sense a HS signal.The HS sensor may take the form of an accelerometer, an acoustic sensor,a microphone, a piezo-based sensor, or other vibrational or acousticsensors. The accelerometer can be a two-axis or a three-axisaccelerometer. Examples of the accelerometer may include flexiblepiezoelectric crystal (e.g., quartz) accelerometer or capacitiveaccelerometer, fabricated using micro electro-mechanical systems (MEMS)technology. The HS sensor may be included in the AMD 110, or disposed ona lead such as a part of the lead system 108. In an example, theaccelerometer may sense an epicardial or endocardial acceleration (EA)signal from a portion of a heart, such as on an endocardial orepicardial surface of one of a left ventricle, a right ventricle, a leftatrium, or a right atrium. The EA signal may contain componentscorresponding to various HS components.

The HS sensor circuit 212 may filter the sensed HS signal through afilter. In an example, the filter may be band-pass filter having apass-band frequency of approximately between 5 and 90 Hz, orapproximately between 9 and 90 Hz. In an example, the filter may includea double or higher-order differentiator configured to calculate a doubleor higher-order differentiation of the heart sound signal. The HSanalyzer circuit may compute an ensemble average of the HS signal overmultiple cardiac cycles, or over a specified time period that isexpected to encompass multiple VM sessions. One or more HS componentsmay be detected from the HS signal, including a first (S1) heart sound,a second (S2) heart sound, a third (S3) heart sound, or a fourth (S4)heart sound using respective time windows. S1 is associated with thevibrational sound made by the heart during tensing of the mitral valve.S2 is produced by the closure of the aortic and pulmonary valves, andmarks the beginning of diastole. S3 is an early diastolic soundcorresponding to passive ventricular filling during diastole, when theblood rushes into the ventricles. S4 is a late diastolic soundcorresponding to active ventricular filling when the atria contract andpush the blood into the ventricles.

The HS sensor circuit 212 may generate one or more HS metrics using thedetected HS components. Examples of the HS metrics may include anintensity (e.g., amplitude or signal energy under the curve) of a HScomponent, or one or more HS-based cardiac timing intervals, such as apre-ejection period (PEP) such as measured between the onset of the QRSto the S1 heart sound, a systolic timing interval (STI) such as measuredbetween the onset of the QRS complex on the ECG to the S2 heart sound, aleft-ventricular ejection time (LVET) such as measured as an intervalbetween S1 and S2 heart sounds, or a diastolic timing interval (DTI)such as measured between the S2 heart sound and the onset of thesubsequent QRS complex on the ECG, among others. These HS-based cardiactiming intervals may be correlated with cardiac contractility or cardiacdiastolic function of the heart. The HS metrics may further includePEP/LVET ratio, STI/DTI ratio, STI/ cycle length (CL) ratio, or DTI/CLratio, or other composite metrics.

The VM-based event detector 220 may be implemented as a part of amicroprocessor circuit, which may be a dedicated processor such as adigital signal processor, application specific integrated circuit(ASIC), microprocessor, or other type of processor for processinginformation including physical activity information. Alternatively, themicroprocessor circuit may be a general-purpose processor that mayreceive and execute a set of instructions of performing the functions,methods, or techniques described herein.

The VM-based event detector 220 may include circuit sets comprising oneor more other circuits or sub-circuits, such as a VM detector 222, aphysiologic response analyzer 224, and a target event detector 226.These circuits may, alone or in combination, perform the functions,methods, or techniques described herein. In an example, hardware of thecircuit set may be immutably designed to carry out a specific operation(e.g., hardwired). In an example, the hardware of the circuit set mayinclude variably connected physical components (e.g., execution units,transistors, simple circuits, etc.) including a computer readable mediumphysically modified (e.g., magnetically, electrically, moveableplacement of invariant massed particles, etc.) to encode instructions ofthe specific operation. In connecting the physical components, theunderlying electrical properties of a hardware constituent are changed,for example, from an insulator to a conductor or vice versa. Theinstructions enable embedded hardware (e.g., the execution units or aloading mechanism) to create members of the circuit set in hardware viathe variable connections to carry out portions of the specific operationwhen in operation. Accordingly, the computer readable medium iscommunicatively coupled to the other components of the circuit setmember when the device is operating. In an example, any of the physicalcomponents may be used in more than one member of more than one circuitset. For example, under operation, execution units may be used in afirst circuit of a first circuit set at one point in time and reused bya second circuit in the first circuit set, or by a third circuit in asecond circuit set at a different time.

The VM detector 222 may detect a VM session, such as a physiologic,naturally occurring VM incidence in an ambulatory patient, using one ormore sensed physiologic signals provided by the sensing circuit 210. Ina non-limiting example, the VM detector 222 may detect a VM sessionusing one or more HS metrics produced by the heart sound sensor circuit212. As discussed above, a typical VM process consists of up to fourtemporal phases each having distinct hemodynamic profiles, such asdistinct blood pressure or heart rate patterns at the VM phases. Thehemodynamic profiles reflect sympathetic and parasympathetic activitiesduring the VM. The present inventors have recognized that various HSmetrics may be indicative of or correlated to the hemodynamic profilesat various VM phases. The VM detector 222 may use the HS metrics todetect an onset, one or more temporal phases, or termination of the VMsession. For example, S1 intensity is correlated to cardiaccontractility, and S2 intensity is correlated to blood pressure. The VMdetector 222 may trend S1 intensity or S2 intensity over a period oftime of approximately 10-30 seconds, and detect a VM session (or a VMphase) using the trended S1 intensity, the trended S2 intensity, or acombined S1 trend and S2 trend.

By way of example and not limitation, the VM detector 222 may detectPhase I of VM using an increase in S1 intensity accompanied by adecrease in S2 intensity. The increase in S1 at Phase I may be resultedfrom an increased venous return, which leads to an increase in cardiaccontractility; and the decrease in S2 represents an initial progressivereduction in blood pressure. The VM detector 222 may detect Phase II ofthe VM using a decrease in S1 intensity and an increase in S2 intensity.The decrease in S1 intensity corresponds to reduced stroke volume andcardiac output, which leads to reduced cardiac contraction. The increasein S2 intensity at Phase II corresponds to the rise in blood pressuredue to vasoconstriction to compensate for the drop in cardiac output.The VM detector 222 may detect Phase IV of the VM using an increase inS1 intensity accompanied by an increase in S2 intensity. Thiscorresponds to the recovery of cardiac output and blood pressure at theclosing phase of VM.

In addition to or in lieu of S1 and S2, in some examples, the VMdetector 222 may detect one or more temporal phases of a VM sessionusing measurements of S3 intensity or S4 intensity. S3 or S4 intensityindicates diastolic function of a heart, and is correlated toleft-ventricular filling pressure or the left atrial pressure (LAP) atthe end of diastole, particularly in a heart failure patient. In anexample, the VM detector 222 may detect Phase I of VM using an increasein S3 intensity or an increase in S4 intensity, which correspond toimmediate accumulation of blood in the left atrium of the heart and thusa rise in LAP. Phase III of VM is characterized by thoracic pressurerelease and widening of intrathoracic arteries and aorta, which may helpreduce LAP and end-diastolic left ventricular pressure. The VM detector222 may detect Phase III using a decrease in S3 intensity or a decreasein S4 intensity. Apart from the intensities S1, S2, S3, or S4 asdiscussed above, other HS metrics, such as PEP, STI, LVET, or othercardiac timing parameters that are correlated with cardiac contractilityor left-ventricular diastolic function, may additionally oralternatively be used to detect a VM session or a particular temporalphase of VM.

The VM detector 222 may detect a VM session, or a portion thereof (e.g.,one or more VM phases), using physiologic information in addition to orin lieu of the HS information as discussed above. The physiologicinformation may be extracted from the received physiologic signal. Invarious examples, the VM detector 222 may detect a VM session usinginformation such as abdominal muscle strain (such as sensed using astrain gauge), respiration information (such as sensed using thoracicimpedance sensor, a flowmeter, or a tracheal noise sensor), heart rateand blood pressure, or information about neural activities. In someexamples, additional sensors may be used to improve signal quality ofthe HS data acquired during the VM session, or to confirm the VM sessiondetected using the HS metrics. Examples of detecting VM using additionalsensors in conjunction with HS information are discussed below, such aswith reference to FIG. 3 .

The physiologic response analyzer 224 may be coupled to the sensingcircuit 210 and the VM detector 222, and configured to detect a patientphysiologic response to the VM session as detected by the VM detector222. In an example, the physiologic response analyzer 224 may use HSsignals to determine the physiologic response to the VM. The HS signalsmay be the same signals used by the VM detector 222 for detecting the VMsession or various VM phases, or different HS signals acquired by thesame HS sensors that provide the HS signal to the VM detector 222. In anexample, the physiologic response analyzer 224 may generate acardiovascular or autonomic function indicator using a comparison of thesensed physiologic signal to a reference VM response (hereinafterreferred to as VM response template). The VM response template may begenerated using physiologic data (e.g., HS data) acquired from thepatient during historical VM sessions, thus representing the patient’sbaseline VM response. Alternatively, the VM response template may begenerated using data from population during the VM sessions, thuspresenting a “normal” VM response. In an example, the physiologicresponse analyzer 224 may determine a degree of deviation of the patientphysiologic data trend (e.g., a S1 intensity trend or a S2 intensitytrend) from the VM response template. The deviation may be computedusing an accumulated difference between the physiologic data trend andthe VM response template over the entirety, or a portion (e.g., one ormore temporal phases), of the VM session. The physiologic responseanalyzer 224 may generate the cardiovascular or autonomic functionindicator indicating a blunted cardiovascular or autonomic function ifthe determined degree of deviation exceeds a threshold.

In some examples, the sensing circuit 210 may sense one or morephysiologic signals in addition to the HS. The physiologic responseanalyzer 224 may determine the physiologic response to the VM using thesensed physiologic signals in lieu of, or in addition to, the HS signal.In an example, the physiologic response analyzer 224 may detect a heartrate (HR) during the detected VM. If the HR falls below a threshold, orif a decreasing trend of HR is detected, an autonomic failure isindicated. Other physiologic signals include cardiac pressure, bloodpressure, cardiac or thoracic impedance, among others.

The target event detector 226 can detect a target physiologic eventusing the detected patient physiologic responses such as provided by thephysiologic response analyzer 224. As discussed above, physiologicresponses to the VM may indicate cardiovascular and autonomousfunctions. The cardiovascular or autonomic function indicator, or thedeviation from a patient baseline VM response template or apopulation-based “normal” VM response template, may be used to formdiagnostics of one or more medical conditions, as to be discussed in thefollowing with reference to FIGS. 4A-4C.

The user interface 230 may include an input unit and an output unit. Inan example, at least a portion of the user interface 230 may beimplemented in the external system 125. The input unit may receive userinput for programming the sensing circuit 210 and the VM-based eventdetector 220, such as parameters for detecting HS components andgenerating HS metrics, threshold values for determining thecardiovascular or autonomic function indicator using the deviation ofphysiologic response to the VM from the reference VM response template,and parameters for detecting the target physiologic event. The inputunit may include a keyboard, onscreen keyboard, mouse, trackball,touchpad, touch-screen, or other pointing or navigating devices. Theoutput unit may include a display for displaying the patient physiologicdata (e.g., the HS signal and the HS metrics), the comparison betweenthe physiologic response to the VM and the reference VM responsetemplate, the detected target events, and any intermediate measurementsor computations, among others. The output unit may also present to auser, such as via a display unit, recommended therapy, such as a changeof parameters in the therapy provided by an implanted device, theprescription to get a device implanted, the initiation or change in adrug therapy, or other treatment options of a patient. The output unitmay include a printer for printing hard copies of signals andinformation of VM response and detected physiologic event. The signalsand information may be presented in a table, a chart, a diagram, or anyother types of textual, tabular, or graphical presentation formats. Thepresentation of the output information may include audio or other mediaformat. In an example, the output unit may generate alerts, alarms,emergency calls, or other forms of warnings to signal the system userabout the detected medical events.

In some examples, the output unit may prompt a user for initiating orrepeating a VM session. This is referred to as a commanded VM session.The sensing circuit 210 and the VM-based event detector 220 may monitorpatient physiologic response to the commanded VM session, and to detecta target event. The commanded VM session may be prompted to the userperiodically, or triggered by a medical event.

The optional therapy circuit 240 may be configured to deliver a therapyto the patient, such as in response to the detected physiologic event,or when the detected cardiovascular or autonomic function indicatorsatisfies a specific condition (e.g., indicating blunted vasovagalresponse or autonomic function). The therapy may be preventive ortherapeutic in nature such as to modify, restore, or improve patientneural, cardiac, or respiratory functions. Examples of the therapy mayinclude electrostimulation therapy delivered to the heart, a nervetissue, other target tissues, a cardioversion therapy, a defibrillationtherapy, or drug therapy including delivering drug to the patient. Insome examples, the therapy circuit 240 may modify an existing therapy,such as adjust a stimulation parameter or drug dosage.

FIG. 3 illustrated generally an example of a portion of a VM detectionsystem that detects a VM session using heart sounds and informationabout patient functional states. By way of example, the patientfunctional states may include one or more of physical activity detectedby a physical activity sensor 312, a posture detected by a posturesensor 314, or respiration detected by a respiration sensor 316. Thephysical activity sensor 312 may include an accelerometer configured tosense a physical activity signal. The accelerometer may be single-axisor multi-axis accelerometer. The posture sensor 314 may include a tiltswitch or a single- or multi-axis accelerometer associated with thepatient. For example, the posture sensor may be disposed external to thebody or implanted inside the body. Posture may be represented by, forexample, a tilt angle. In some examples, posture or physical activityinformation may be derived from thoracic impedance information. Therespiration sensor may include a flowmeter that directly senses airflowin the respiratory system or volume change in the lung, a strain sensorconfigured to sense changes in chest muscle tension corresponding torespiration cycles, an accelerometer to measure acceleration associatedwith displacement or movement of chest walls corresponding torespiration, or an impedance sensor to sense thoracic impedance that ismodulated by respiration.

One or more of the physical activity sensor 312, the posture sensor 314,or the respiration sensor 316 may be associated with a patient invarious manners, such as implantable sensors configured for subcutaneousimplantation at various body locations, or wearable sensors configuredto be worn on the head, wrist, hand, foot, ankle, waist, or other partsof the body. One or more of these sensors may be used as a confirmationof patient initiating a VM session, or to improve quality of the HS dataacquired during the VM session. For example, a low activity level, asdetected by the physical activity sensor 312, may rule out strenuousbreathing during moderate to high physical activity, as VM typicallyoccurs when patient remains at low activity. Similarly, an uprightposture is to rule out VM confounders, such as sleep apnea that mayinvolve strenuous breathing or breathing pause during sleep. In anexample, the heart sound sensor 212 is configured to acquire HS datawhen the physical activity sensor 312 detects a low activity level(e.g., below a threshold), the posture sensor 314 detects an uprightposture, or the respiration sensor 316 detects forced breathing.Additionally or alternatively, the VM detector 222 may select portionsof the HS signal acquired by the HS sensor 212 only when the lowactivity level, upright posture, and forced breathing are detected bythe respective sensors. By using information of physical activity,posture, and detected respiration, fewer false positive detections of VMsessions may result.

FIGS. 4A-C illustrate generally examples of VM-based physiologic eventdetectors 410, 420, and 430 configured to detect various physiologicevents using physiologic response to the VM. The detectors 410, 420, and430 are embodiments of the VM-based event detector 220 as illustrated inFIG. 2 . FIG. 4A illustrates a VM-based event detector 410 configured todetect a target event of worsening heart failure (WHF) using thephysiologic responses to the VM. The VM-based event detector 410includes a diastolic function analyzer 414, which is an embodiment ofthe physiologic response analyzer 224, and configured to generate acardiac diastolic function indicator during the detected VM.Cardiovascular response to the VM has been found to be significantlycorrelated with ventricular filling pressures in HF patients. Anabnormal response to the VM in cardiac patients may be closelyassociated with clinical signs and symptoms of congestive HF. In anexample, the diastolic function analyzer 414 may generate a diastolicfunction indicator using a HS metric, such as an S3 intensity or an S4intensity. In an example, the diastolic function analyzer 414 maycompute a deviation of an S3 intensity trend (or an S4 intensity trend)acquired during a detected VM session from a reference S3 template (or areference S4 template), and the WHF detector 416 may detect an WHF eventwhen the computed deviation satisfies a specified condition, such asexceeding a threshold. The deviation may be computed throughout the VMsession, or during one or more VM phases, such as Phase II which is moreclosely associated with the signs of WHF in HF patients.

The diastolic function indicator may be represented by a linear ornonlinear combination of S3 and S4 metrics. In an example, the diastolicfunction analyzer 414 may compute a ratio of an S3 intensity to an S4intensity (S3/S4 ratio). The S3 intensity and S4 may respectivelycorrespond to the “E” wave and “A” wave as seen in a Dopplerechocardiograph. The “E” wave and “A” wave are two peaks on thetransmitral flow profile derived from the echocardiograph. The “E” wavearises due to early passive diastolic filling, which accounts for 70-75%of the ventricular filling during this phase. The “A” wave arises due toatrial contraction, forcing approximately 20-25% of stroke volume intothe ventricle. A ratio of “E” wave to “A” wave (hereinafter the “E/Aratio”) represents a relative velocity of blood flow during the earlyand late phases of diastole. In a subject with normal diastolicfunction, the E/A ratio is within a range of approximately between 1 and1.5. In HF patients with impaired relaxation (a relatively milddiastolic dysfunction), the left ventricular wall can become stiff suchthat it impairs proper filling. The “E” wave may become reduced,representing a transmitral velocity that may be even slower than thesubsequent “A” wave velocity. Correspondingly, the E/A ratio may be lessthan one.

The S3/S4 ratio may be indicative of or correlated to the E/A ratio. Inan example, the WHF detector may compare the S3/S4 ratio obtained duringthe VM to a healthy value range defined by a lower threshold value and ahigher threshold value. The WHF detector 416 may detect WHF when theS3/S4 satisfies a specific condition, such as exceeding a thresholdvalue or falls within a specified value range. For example, if S3/S4ratio falls within the healthy value range, then no substantialdiastolic dysfunction is detected. If S3/S4 exceeds the upper thresholdvalue, restrictive ventricular filling is indicated. If S3/S4 fallsbelow the lower threshold value, impaired diastolic function isindicated.

FIG. 4B illustrates a VM-based event detector 420 configured to detect atarget event of syncope using the physiologic responses to the VM. Aspreviously discussed, majority of syncope are non-cardiac in nature,including neurally mediated syncope (or vasovagal syncope, WS), andorthostatic syncope (or orthostatic hypotension, OH). The VVS is adisorder of the autonomic regulation of postural tone, and may berelated to vasovagal, carotid sinus, or situational causes ofhypotension.

The VM-based event detector 420 includes autonomic function analyzer424, which is an embodiment of the physiologic response analyzer 224,coupled to the VM detector 222 and configured to detect a cardiovascularor autonomic function indicator during the detected VM. In one example,the cardiovascular or autonomic function indicator includes a Valsalvaratio, which generally refers to a ratio of the longest cardiac cycle(R-R interval) at Phase IV of the VM following the liberation ofstraining to the shortest cardiac cycle at Phase II of the VM duringstraining (RR_(IV)/RR_(II)). The Valsalva ratio reflects bothparasympathetic (vagal) and sympathetic function. The normal HR responseduring the VM is an increase in HR (i.e., shortening of RR interval)during Phase II in response to the fall in blood pressure, and thebaroreflex response to the blood pressure overshoot in Phase IV istransient bradycardia (i.e., a decrease in HR or lengthening of RRinterval). In VVS patients, there can be a loss of both the bloodpressure overshoot and the reflex bradycardia, thereby a lower thannormal Valsalva ratio. The autonomic function analyzer 424 may computethe Valsalva ratio using heart rates (or RR intervals) measured duringthe detected VM session, and the syncope detector 426 may detect the VVSwhen the computed Valsalva ratio satisfies a specific condition, such asfalling below a threshold or falls within a value range. An example ofthe Valsalva ratio threshold is approximately between 1.1 and 1.2.

The syncope detector 426 may also differentially diagnose orthostaticsyncope (or OH), which is clinically a confounder of VVS. Compared to ahealthy subject, a patient with OH may not be able to generateappropriate sympathetically mediated vasoconstriction in response to theinitial hypotension at Phase I. Patients with OH also lack bloodpressure recovery at the late Phase II, and the blood pressure overshootat Phase IV. Rather, the BP slowly drifts back up to baseline after theValsalva-induced hypotension. The autonomic function analyzer 424 maygenerate the cardiovascular or autonomic function indicator using a HSmetric, such as S2 intensity. S2 intensity is correlated with bloodpressure during the VM. The vasovagal function analyzer 424 maydetermine abnormality of S2 response, such as computing a deviation of aS2 intensity trend during the detected VM (or during one or more VMphases) from a reference S2 intensity template acquired from healthypopulation. The syncope detector 426 may detect orthostatic syncope ifthe deviation of S2 intensity from the template satisfies a specifiedcondition, such as exceeding a threshold.

FIG. 4C illustrates a VM-based event detector 430 is configured todetect a constipation episode using the detected physiologic responsesto VM.. Constipation generally refers to difficulty or slowing ofpassing the stool and less frequent (e.g., three or fewer in a week)bowel movements than normal. A VM session is typically invoked duringdefecation. During VM, with the holding of the breath and straining, thediaphragm is forced downwards by the increased pressure inside thethoracic cavity, thereby helping evacuating waste When constipationoccurs, excessive straining, expressed in intensively repeated VM, isneeded for emptying the bowels. The increased pressure in the thoraciccavity reduces the amount of blood flowing into the thoracic cavity,especially in the veins leading to the right atrium of the heart.Although a healthy subject may withstand the intensive and repeatedstraining at defecation, for a cardiac patient (e.g., HF) withcompromised cardiovascular system, constipation may increase the risk ofdefecation syncope attack or death. The intensive and repeated VM duringconstipation may also cause blood clots to detach, bleeding, irregularheart rhythms and cardiac arrest.

The VM-based event detector 430 may be used to monitor bowel movementregularity and assess severity of constipation. The VM-based eventdetector 430 includes the physiologic response analyzer 224 couple tothe VM detector 222, and a constipation detector 436 configured toconstipation. In an example, the VM detector 222 may detect onset of aVM session, such as by using HS metrics. The physiologic responseanalyzer 224 may determine duration of a VM session, or frequency of VMsessions such as by counting the VM sessions as detected by the VMdetector 222 during a specified time period. The constipation detector436 may detect a constipation episode, or to generate a constipationseverity indicator, using the frequency of VM and duration of each VMsession. For example, frequent VM sessions that sustained for anextended period of time, with each VM having a short duration, may beindicative of an incidence of constipation.

The physiologic response analyzer 224 may additionally or alternativelydetermine, using HS metrics or other physiologic signals (e.g., heartrate or blood pressure signal), the hemodynamic responses during thestraining (e.g., Phases I- II) and relaxation (e.g., Phases III-IV) ofeach detected VM session. In an example, the physiologic responseanalyzer 224 may determine changes in heart rate (HR) or changes in HSmetrics (e.g., S1 or S2 intensity) at one or more VM phases, or durationof one or more VM phases, such as the straining period (e.g., Phases Iand II) of the VM. A more severe constipation may be accompanied by moresignificant hemodynamic change from a reference baseline, or asubstantially longer straining period of a VM. The constipation detector436 may determine the constipation severity indicator using a comparisonof the determined changes in HR or the change in HS metrics torespective thresholds, or a comparison of straining period (e.g.,duration of Phases I and II) of a VM session to a threshold.

FIG. 5 illustrates generally an example of a method 500 for monitoring aphysiologic response to VM in a patient. In an example, the method 500may be implemented in and executed by the cardiac arrhythmia detectioncircuit 160 in the AMD 110, the external system 130, or the VM detectorand analyzer system 200.

The method 500 commences at step 510, where one or more physiologicsignals including a heart sounds (HS) signal may be received. The HSsignal may be sensed using a HS sensor, such as an accelerometer, anacoustic sensor, a microphone, a piezo-based sensor, or othervibrational or acoustic sensors that are included in the AMD 110, ordisposed on a lead such as a part of the lead system 108. In an example,the accelerometer may sense an epicardial or endocardial acceleration(EA) signal from a portion of a heart, such as on an endocardial orepicardial surface of one of a left ventricle, a right ventricle, a leftatrium, or a right atrium. Other physiologic signal may also bereceived, which may include surface ECG, subcutaneous ECG, intracardiacEGM, heart rate signal, physical activity signal, or posture signal, athoracic or cardiac impedance signal, blood pressure signal, bloodoxygen saturation signal, physiologic response to activity, apneahypopnea index, one or more respiration signals such as a respirationrate signal or a tidal volume signal, brain natriuretic peptide (BNP),blood chemical levels, etc.

At 520, a VM session may be detected using at least the received HSsignal, such as by using the VM detector 222. The VM session may occurnaturally in an ambulatory setting. One or more HS components may bedetected from the HS signal, including a first (S1) heart sound, asecond (S2) heart sound, a third (S3) heart sound, or a fourth (S4)heart sound using respective time windows. One or more HS metrics may begenerated using the detected HS components, which may include, by way ofexample and not limitation, an intensity (e.g., amplitude or signalenergy under the curve) of a HS component, one or more HS-based cardiactiming intervals such as PEP, STI, LVET, DTI, as discussed above withreference toFIG. 2 , or composite HS metrics.

Various HS metrics may be indicative of or correlated with thehemodynamic profiles at various VM phases, including one or more ofPhases I-IV. In an example, Phase I of VM may be recognized using anincrease in S1 intensity accompanied by a decrease in S2 intensity.Additionally or alternatively, an increase in S3 intensity or anincrease in S4 intensity, which correspond to immediate accumulation ofblood in the left atrium of the heart and thus a rise in LAP, may alsobe used to detect VM Phase I. In an example, Phase II of the VM may berecognized using a decrease in S1 intensity and an increase in S2intensity. The decrease in S1 intensity corresponds to reduced strokevolume and cardiac output, which leads to reduced cardiac contraction.The increase in S2 intensity at Phase II corresponds to the rise inblood pressure due to vasoconstriction to compensate for the drop incardiac output. Phase III of VM is characterized by thoracic pressurerelease, and widening of intrathoracic arteries and aorta. In anexample, Phase III of VM may be recognized using a decrease in S3intensity or a decrease in S4 intensity. which reduces LAP andend-diastolic left ventricular pressure. S3 and S4 intensity may eachindicate diastolic function of a heart, and is correlated toleft-ventricular filling pressure or the left atrial pressure (LAP) atthe end of diastole. In another example, Phase IV of the VM may berecognized using an increase in S1 intensity accompanied by an increasein S2 intensity. This corresponds to the recovery of cardiac output andblood pressure at the closing phase of VM.

Additional physiologic information may be used to improve the HS-basedVM session. For example, physical activity, posture, or respiration rateor pattern, as discussed above with reference to FIG. 3 , may be used toconfirm a VM session, or to improve quality of the HS data acquiredduring the VM session. In an example, detection of VM or one or more VMphases based on HS may be initiated when a low activity level, anupright posture, or a forced breathing have been detected. Using theinformation of physical activity, posture, or respiration may helpreduce false positive detections of VM sessions

At 530, physiologic response to the VM session may be sensed, such as byusing the physiologic response analyzer 224. Heart sounds, either thesame signals used for detecting the VM session, or different HS signalsacquired by the same HS sensors that provide the HS signal for detectingthe VM session, may be used to characterize the physiologic response tothe detected VM. In an example, a cardiovascular or autonomic functionindicator may be generated based on a comparison of the sensedphysiologic signal to a reference VM response, also referred to as a VMresponse template. The VM response template may be generated usingphysiologic data (e.g., HS data) acquired from the patient duringhistorical VM sessions, thus representing the patient’s baseline VMresponse. Alternatively, the VM response template may be generated usingdata from population during the VM sessions, thus presenting a “normal”VM response. The cardiovascular or autonomic function indicator may berepresented by a degree of deviation (e.g., accumulated difference overtime) of the patient physiologic data trend (e.g., a S1 intensity trendor a S2 intensity trend) from the VM response template.

At 540, a target physiologic event may be detected using the patientphysiologic response to VM (e.g., the cardiovascular or autonomicfunction indicator as discussed above), such as by using the targetevent detector 226. In an example, S3 and S4 heart sound components maybe detected from a HS signal sensed during the detected VM session. Adiastolic dysfunction indictor may be generated using a ratio of the S3intensity to the S4 intensity. The S3/S4 ratio may be indicative of orcorrelated to the E/A ratio, a metric in Doppler echocardiograph thatrepresents a relative velocity of blood flow during the early and latephases of diastole. A WHF event may be detected using the generateddiastolic dysfunction indictor.

The cardiovascular or autonomic function indicator generated at 530 maybe used to detect a syncope or pre-syncope event. An example of thecardiovascular or autonomic function indicator includes a Valsalvaratio, that is, a ratio of the longest cardiac cycle (R-R interval) atPhase IV of the VM following the liberation of straining to the shortestcardiac cycle at Phase II of the VM during straining (RR_(IV)/RR_(II)).A vasovagal syncope (WS) may be detected when the computed Valsalvaratio satisfies a specific condition, such as falling below a thresholdor falling below a threshold or falls within a value range. In anotherexample, the cardiovascular or autonomic function indicator includes S2intensity, which is correlated with blood pressure during the VM. Anorthostatic syncope (or orthostatic hypotension, OH) may be detected ifthe deviation of S2 intensity from the VM response template satisfies aspecified condition, such as exceeding a threshold.

Additionally or alternatively, a constipation episode may be detectedusing the detected physiologic responses to VM at 540. When constipationoccurs, excessive straining, expressed in intensively repeated VM, isneeded for emptying the bowels. The increased pressure in the thoraciccavity reduces the amount of blood flowing into the thoracic cavity,especially in the veins leading to the right atrium of the heart, andincrease the risk of defecation syncope attack or death for patientswith compromised cardiovascular system. Onset, duration, and frequencyof repeated VM sessions may be detected such as using the HS metrics asdiscussed above. Constipation severity may be quantified using, forexample, frequency of VM and duration of each VM session. For example,more frequent VM sessions that sustained for an extended period of time,with each VM having a short duration, may be indicative more severeconstipation condition.

The detected VM session, the physiologic response to VM, and thedetected target physiologic event, may be provided to one or more of theprocesses 552, 554, or 556. At 552, the detected VM and the detectedphysiologic event, among other information, may be output to a user,such as displayed on a display unit of the user interface 230. In someexamples, a hard copy of the detection information may be generated. Invarious examples, alerts, alarms, emergency calls, or other forms ofwarnings to signal may be generated to warn the system user about thedetected target event. At 554, a recommendation may be generated andprovided to a user. The recommendation may include one or more offurther diagnostic tests to be performed, initiating a therapy to treatthe detected event, changing parameters in the therapy provided by animplanted device, the prescription to get a device implanted, theinitiation or change in a drug therapy, or other treatment options of apatient. At 556, a therapy may be delivered to the patient in responseto the detected physiologic event, or when the detected cardiovascularor autonomic function indicator satisfies a specific condition (e.g.,indicating a blunted vasovagal response or autonomic function), such asvia the optional therapy circuit 240 as illustrated in FIG. 2 . Examplesof the therapy may include electrostimulation therapy delivered to theheart, a nerve tissue, other target tissues, a cardioversion therapy, adefibrillation therapy, or drug therapy including delivering drug to thepatient. In some examples, the therapy circuit 240 may modify anexisting therapy, such as adjust a stimulation parameter or drug dosage.

FIG. 6 illustrates generally a block diagram of an example machine 600upon which any one or more of the techniques (e.g., methodologies)discussed herein may perform. Portions of this description may apply tothe computing framework of various portions of the LCP device, the AMD,or the external programmer.

In alternative embodiments, the machine 600 may operate as a standalonedevice or may be connected (e.g., networked) to other machines. In anetworked deployment, the machine 600 may operate in the capacity of aserver machine, a client machine, or both in server-client networkenvironments. In an example, the machine 600 may act as a peer machinein peer-to-peer (P2P) (or other distributed) network environment. Themachine 600 may be a personal computer (PC), a tablet PC, a set-top box(STB), a personal digital assistant (PDA), a mobile telephone, a webappliance, a network router, switch or bridge, or any machine capable ofexecuting instructions (sequential or otherwise) that specify actions tobe taken by that machine. Further, while only a single machine isillustrated, the term “machine” shall also be taken to include anycollection of machines that individually or jointly execute a set (ormultiple sets) of instructions to perform any one or more of themethodologies discussed herein, such as cloud computing, software as aservice (SaaS), other computer cluster configurations.

Examples, as described herein, may include, or may operate by, logic ora number of components, or mechanisms. Circuit sets are a collection ofcircuits implemented in tangible entities that include hardware (e.g.,simple circuits, gates, logic, etc.). Circuit set membership may beflexible over time and underlying hardware variability. Circuit setsinclude members that may, alone or in combination, perform specifiedoperations when operating. In an example, hardware of the circuit setmay be immutably designed to carry out a specific operation (e.g.,hardwired). In an example, the hardware of the circuit set may includevariably connected physical components (e.g., execution units,transistors, simple circuits, etc.) including a computer readable mediumphysically modified (e.g., magnetically, electrically, moveableplacement of invariant massed particles, etc.) to encode instructions ofthe specific operation. In connecting the physical components, theunderlying electrical properties of a hardware constituent are changed,for example, from an insulator to a conductor or vice versa. Theinstructions enable embedded hardware (e.g., the execution units or aloading mechanism) to create members of the circuit set in hardware viathe variable connections to carry out portions of the specific operationwhen in operation. Accordingly, the computer readable medium iscommunicatively coupled to the other components of the circuit setmember when the device is operating. In an example, any of the physicalcomponents may be used in more than one member of more than one circuitset. For example, under operation, execution units may be used in afirst circuit of a first circuit set at one point in time and reused bya second circuit in the first circuit set, or by a third circuit in asecond circuit set at a different time.

Machine (e.g., computer system) 600 may include a hardware processor 602(e.g., a central processing unit (CPU), a graphics processing unit(GPU), a hardware processor core, or any combination thereof), a mainmemory 604 and a static memory 606, some or all of which may communicatewith each other via an interlink (e.g., bus) 608. The machine 600 mayfurther include a display unit 610 (e.g., a raster display, vectordisplay, holographic display, etc.), an alphanumeric input device 612(e.g., a keyboard), and a user interface (UI) navigation device 614(e.g., a mouse). In an example, the display unit 610, input device 612and UI navigation device 614 may be a touch screen display. The machine600 may additionally include a storage device (e.g., drive unit) 616, asignal generation device 618 (e.g., a speaker), a network interfacedevice 620, and one or more sensors 621, such as a global positioningsystem (GPS) sensor, compass, accelerometer, or other sensor. Themachine 600 may include an output controller 628, such as a serial(e.g., universal serial bus (USB), parallel, or other wired or wireless(e.g., infrared (IR), near field communication (NFC), etc.) connectionto communicate or control one or more peripheral devices (e.g., aprinter, card reader, etc.).

The storage device 616 may include a machine readable medium 622 onwhich is stored one or more sets of data structures or instructions 624(e.g., software) embodying or utilized by any one or more of thetechniques or functions described herein. The instructions 624 may alsoreside, completely or at least partially, within the main memory 604,within static memory 606, or within the hardware processor 602 duringexecution thereof by the machine 600. In an example, one or anycombination of the hardware processor 602, the main memory 604, thestatic memory 606, or the storage device 616 may constitute machinereadable media.

While the machine readable medium 622 is illustrated as a single medium,the term “machine readable medium” may include a single medium ormultiple media (e.g., a centralized or distributed database, and/orassociated caches and servers) configured to store the one or moreinstructions 624.

The term “machine readable medium” may include any medium that iscapable of storing, encoding, or carrying instructions for execution bythe machine 600 and that cause the machine 600 to perform any one ormore of the techniques of the present disclosure, or that is capable ofstoring, encoding or carrying data structures used by or associated withsuch instructions. Non-limiting machine readable medium examples mayinclude solid-state memories, and optical and magnetic media. In anexample, a massed machine readable medium comprises a machine readablemedium with a plurality of particles having invariant (e.g., rest) mass.Accordingly, massed machine-readable media are not transitorypropagating signals. Specific examples of massed machine readable mediamay include: non-volatile memory, such as semiconductor memory devices(e.g., Electrically Programmable Read-Only Memory (EPROM), ElectricallyErasable Programmable Read-Only Memory (EEPROM)) and flash memorydevices; magnetic disks, such as internal hard disks and removabledisks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

The instructions 624 may further be transmitted or received over acommunications network 626 using a transmission medium via the networkinterface device 620 utilizing any one of a number of transfer protocols(e.g., frame relay, internet protocol (IP), transmission controlprotocol (TCP), user datagram protocol (UDP), hypertext transferprotocol (HTTP), etc.). Example communication networks may include alocal area network (LAN), a wide area network (WAN), a packet datanetwork (e.g., the Internet), mobile telephone networks (e.g., cellularnetworks), Plain Old Telephone (POTS) networks, and wireless datanetworks (e.g., Institute of Electrical and Electronics Engineers (IEEE)802.11 family of standards known as WiFi®, IEEE 802.16 family ofstandards known as WiMax®), IEEE 802.15.4 family of standards,peer-to-peer (P2P) networks, among others. In an example, the networkinterface device 620 may include one or more physical jacks (e.g.,Ethernet, coaxial, or phone jacks) or one or more antennas to connect tothe communications network 626. In an example, the network interfacedevice 620 may include a plurality of antennas to wirelessly communicateusing at least one of single-input multiple-output (SIMO),multiple-input multiple-output (MIMO), or multiple-input single-output(MISO) techniques. The term “transmission medium” shall be taken toinclude any intangible medium that is capable of storing, encoding orcarrying instructions for execution by the machine 600, and includesdigital or analog communications signals or other intangible medium tofacilitate communication of such software.

Various embodiments are illustrated in the figures above. One or morefeatures from one or more of these embodiments may be combined to formother embodiments.

The method examples described herein can be machine orcomputer-implemented at least in part. Some examples may include acomputer-readable medium or machine-readable medium encoded withinstructions operable to configure an electronic device or system toperform methods as described in the above examples. An implementation ofsuch methods may include code, such as microcode, assembly languagecode, a higher-level language code, or the like. Such code may includecomputer readable instructions for performing various methods. The codecan form portions of computer program products. Further, the code can betangibly stored on one or more volatile or non-volatilecomputer-readable media during execution or at other times.

The above detailed description is intended to be illustrative, and notrestrictive. The scope of the disclosure should therefore be determinedwith references to the appended claims, along with the full scope ofequivalents to which such claims are entitled.

What is claimed is:
 1. A medical-device system, comprising: a Valsalvamaneuver (VM) detector circuit configured to detect a VM session using aheart sound signal sensed from a patient; and a physiologic eventdetector circuit configured to generate a diastolic function indictorusing physiologic information sensed from the patient during thedetected VM session, and to detect a worsening heart failure (WHF) eventbased at least in part on the generated diastolic function indictor. 2.The medical-device system of claim 1, wherein the physiologic eventdetector circuit is configured to determine a heart sound componentusing the sensed heart sound signal, and to generate the diastolicfunction indictor using the determined heart sound component.
 3. Themedical-device system of claim 2, wherein the determined heart soundcomponent includes an S3 intensity.
 4. The medical-device system ofclaim 3, wherein the physiologic event detector circuit is configured todetect the WHF event in response to the S3 intensity exceeding areference S3 intensity by a specific margin.
 5. The medical-devicesystem of claim 2, wherein the determined heart sound component includesa combination of an S3 intensity and an S4 intensity.
 6. Themedical-device system of claim 5, wherein the determined heart soundcomponent includes a ratio of the S3 intensity to the S4 intensity,wherein the physiologic event detector circuit is configured todetermine an indicator of impaired diastolic function in response to thedetermined ratio of the S3 intensity to the S4 intensity falling below afirst threshold value lower than a baseline value range, and to detectthe WHF event based at least in part on the impaired diastolic function.7. The medical-device system of claim 5, wherein the physiologic eventdetector circuit is configured to determine an indicator of restrictiveventricular filling in response to the determined ratio of the S3intensity to the S4 intensity exceeding a second threshold value greaterthan a baseline value range, and to detect the WHF event based at leastin part on the restrictive ventricular filling.
 8. The medical-devicesystem of claim 2, wherein the determined heart sound component includesa cardiac timing parameter including at least one of: a pre-ejectionperiod; a systolic timing interval; a left-ventricular ejection time; ora diastolic timing interval.
 9. The medical-device system of claim 1,wherein the VM detector circuit is configured to determine one or moreVM phases using the sensed heart sound signal, wherein the physiologicevent detector circuit is configured to generate the diastolic functionindictor during at least one of the determined one or more VM phases.10. The medical-device system of claim 9, wherein the VM detectorcircuit is configured to determine the one or more VM phases using anincrease or decrease trend of one or more of an S1 intensity, an S2intensity, an S3 intensity, or an S4 intensity.
 11. The medical-devicesystem of claim 1, further comprising a therapy circuit configured toinitiate or adjust a therapy to the patient in response to the detectionof the WHF event.
 12. A method detecting a cardiac event in a patient,the method comprising: detecting, using a Valsalva maneuver (VM)detector circuit, a VM session using a heart sound signal sensed fromthe patient; generating, using a physiologic event detector circuit, adiastolic function indictor using physiologic information sensed fromthe patient during the detected VM session; and detecting a worseningheart failure (WHF) event based at least in part on the generateddiastolic function indictor.
 13. The method of claim 12, comprisingdetermining a heart sound component using the sensed heart sound signal,wherein generating the diastolic function indictor includes using thedetermined heart sound component.
 14. The method of claim 13, whereinthe determined heart sound component includes an S3 intensity, whereindetecting the WHF event is in response to the S3 intensity exceeding areference S3 intensity by a specific margin.
 15. The method of claim 13,wherein the determined heart sound component includes a ratio of an S3intensity to an S4 intensity, and wherein generating the diastolicfunction indictor includes determining an indicator of impaireddiastolic function in response to the determined ratio of the S3intensity to the S4 intensity falling below a first threshold valuelower than a baseline value range, wherein detecting the WHF event isbased at least in part on the impaired diastolic function.
 16. Themethod of claim 13, wherein the determined heart sound componentincludes a ratio of an S3 intensity to an S4 intensity, the methodfurther comprising: determining an indicator of restrictive ventricularfilling in response to the determined ratio of the S3 intensity to theS4 intensity exceeding a second threshold value greater than a baselinevalue range; and detecting the WHF event based at least in part on therestrictive ventricular filling.
 17. The method of claim 13, wherein thedetermined heart sound component includes a cardiac timing parameterincluding at least one of: a pre-ejection period; a systolic timinginterval; a left-ventricular ejection time; or a diastolic timinginterval.
 18. The method of claim 12, comprising determining one or moreVM phases using the sensed heart sound signal, wherein generating thediastolic function indictor includes using the sensed heart sound signalduring at least one of the determined one or more VM phases.
 19. Themethod of claim 18, wherein determining the one or more VM phases isbased at least in part on an increase or decrease trend of one or moreof an S1 intensity, an S2 intensity, an S3 intensity, or an S4intensity.
 20. The method of claim 12, further comprising initiating oradjusting a therapy to the patient in response to the detection of theWHF event.